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2026

Kākāpō Cam: Rakiura live stream (via) Critical update for this year's Kākāpō breeding season: the New Zealand Department of Conservation have a livestream running of Rakiura's nest!

You’re looking at the underground nest of 23-year-old Rakiura. She has chosen this same site to nest for all seven breeding seasons since 2008, a large cavity under a rātā tree. Because she returns to the site so reliably, we’ve been able to make modifications over the years to keep it safe and dry, including adding a well-placed hatch for monitoring eggs and chicks.

Rakiura is a legendary Kākāpō:

Rakiura hatched on 19 February 2002 on Whenua Hou/Codfish Island. She is the offspring of Flossie and Bill. Her name comes from the te reo Māori name for Stewart Island, the place where most of the founding kākāpō population originated.

Rakiura has nine living descendants, three females and six males, across six breeding seasons. In 2008 came Tōitiiti, in 2009 Tamahou and Te Atapō, in 2011 Tia and Tūtoko, in 2014 Taeatanga and Te Awa, in 2019 Mati-mā and Tautahi. She also has many grandchicks.

She laid her first egg of the season at 4:30pm NZ time on 22nd January. The livestream went live shortly afterwards, once she committed to this nest.

The stream is on YouTube. I used Claude Code to write a livestream-gif.py script and used that to capture this sped-up video of the last few hours of footage, within which you can catch a glimpse of the egg!

# 25th January 2026, 4:53 am / youtube, kakapo, conservation, claude-code

LLM predictions for 2026, shared with Oxide and Friends

Visit LLM predictions for 2026, shared with Oxide and Friends

I joined a recording of the Oxide and Friends podcast on Tuesday to talk about 1, 3 and 6 year predictions for the tech industry. This is my second appearance on their annual predictions episode, you can see my predictions from January 2025 here. Here’s the page for this year’s episode, with options to listen in all of your favorite podcast apps or directly on YouTube.

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2025

The new ChatGPT Images is here. OpenAI shipped an update to their ChatGPT Images feature - the feature that gained them 100 million new users in a week when they first launched it back in March, but has since been eclipsed by Google's Nano Banana and then further by Nana Banana Pro in November.

The focus for the new ChatGPT Images is speed and instruction following:

It makes precise edits while keeping details intact, and generates images up to 4x faster

It's also a little cheaper: OpenAI say that the new gpt-image-1.5 API model makes image input and output "20% cheaper in GPT Image 1.5 as compared to GPT Image 1".

I tried a new test prompt against a photo I took of Natalie's ceramic stand at the farmers market a few weeks ago:

Add two kakapos inspecting the pots

Outdoor craft market booth displaying handmade ceramics and jewelry on a navy tablecloth with "NATBAT CREATIONS CALIFORNIA USA" logo. Items include colorful glazed ceramic cups in blue, orange, and black; decorative bowls including a rainbow-striped piece; jewelry pendants and earrings on wooden display stands; ceramic plant markers in various colors labeled "Artichoke", "Cilantro", "Chili", "Oregano", "Potato", "Pumpkin", "Sage".

Here's the result from the new ChatGPT Images model:

Same craft market booth as previous image, now with two large olive-green Kākāpō parrots perched on the table among the ceramics, one investigating the blue glazed cups and the other examining an orange cup.

And here's what I got from Nano Banana Pro:

Same craft market booth with two Kākāpō now in different positions: one remains center-table peering into the ceramic cups near the rainbow pot, while the second has moved to the right edge of the table near the plant markers, appearing to examine or possibly chew on items at the table's corner. They are both a little smaller than in the first image.

The ChatGPT Kākāpō are a little chonkier, which I think counts as a win.

I was a little less impressed by the result I got for an infographic from the prompt "Infographic explaining how the Datasette open source project works" followed by "Run some extensive searches and gather a bunch of relevant information and then try again" (transcript):

Infographic titled "HOW DATASETTE WORKS" with subtitle "THE OPEN SOURCE DATA PLATFORM" showing a four-step workflow. STEP 1 (orange): "LOAD YOUR DATA" - "CSV, JSON, XLSX, SQLite, PostgreSQL, etc." with icons of file types flowing into a laptop. Below: "IMPORT DATASETS - Turn your structured data into SQLite databases and .db files." with checkmarks for "Datasette Desktop App for local deployment", "CLI tool for command-line imports", "Automatic CSV import tool". STEP 2 (green): "PUBLISH & DEPLOY" - "HOST DATASETS ONLINE" with cloud and server icons labeled "DEPLOY". Below: "SHARE ONLINE - Deploy your Datasette instance to a public server." with checkmarks for "Datasette Cloud - Free hosting service", "Deploy anywhere via plugins", "Configurable API tools". STEP 3 (purple): "EXPLORE & QUERY" - "BROWSE, SEARCH & VISUALIZE" with database and browser window icons. Below: "SQL QUERIES & SEARCH - Browse, filter, search, and visualize your data with an interactive web interface." with checkmarks for "Perform SQL queries directly from the browser", "Filter, sort, and facet data", "Generate custom visualizations and charts". STEP 4 (red): "BUILD & EXTEND" - "PLUGINS, APIS & INTEGRATIONS" with gear and wrench icons labeled "API". Below: "CUSTOMIZE & DEVELOP" with bullets "Develop custom plugins for added functionality", "Access JSON API for programmatic queries", "Embed and integrate Datasette into other applications". Bottom banner shows four features: "OPEN DATA PLATFORM - Widely used for visualizing, sharing and building applications with SQLite backed data", "EXTENSIBLE PLUGINS - 100+ plugins available, inc uding chaps, charts authentication, and more", "ACCESS CONTROL - Granular permissions for controlling who s an access and interact with your data", "OPEN SOURCE PROJECT - Actively developed open source project with a vibrant community of contributors".

See my Nano Banana Pro post for comparison.

Both models are clearly now usable for text-heavy graphics though, which makes them far more useful than previous generations of this technology.

Update 21st December 2025: I realized I already have a tool for accessing this new model via the API. Here's what I got from the following:

OPENAI_API_KEY="$(llm keys get openai)" \
  uv run openai_image.py -m gpt-image-1.5\
  'a raccoon with a double bass in a jazz bar rocking out'

Digital artwork of a raccoon wearing a black fedora and vest, passionately playing an upright double bass on stage at a dimly lit jazz club. The raccoon's mouth is open as if singing. A vintage microphone stands to the right, another raccoon musician is visible in the background, and a neon sign reading "Jazz Club" glows in warm orange letters. The scene has a smoky, atmospheric quality with rich amber and brown tones.

Total cost: $0.2041.

# 16th December 2025, 11:59 pm / ai, kakapo, openai, generative-ai, text-to-image, nano-banana

OpenAI are quietly adopting skills, now available in ChatGPT and Codex CLI

Visit OpenAI are quietly adopting skills, now available in ChatGPT and Codex CLI

One of the things that most excited me about Anthropic’s new Skills mechanism back in October is how easy it looked for other platforms to implement. A skill is just a folder with a Markdown file and some optional extra resources and scripts, so any LLM tool with the ability to navigate and read from a filesystem should be capable of using them. It turns out OpenAI are doing exactly that, with skills support quietly showing up in both their Codex CLI tool and now also in ChatGPT itself.

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2019

In Kākāpō breeding season news…. I posted on MetaFilter about this year’s record-breaking Kākāpō breeding season.

# 19th April 2019, 3:11 am / metafilter, kakapo, conservation